Waste Management Dataset Profiling Report

Brought to you by YData

Dataset statistics

Number of variables	13
Number of observations	850
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	337.7 KiB
Average record size in memory	406.8 B

Variable types

Categorical	6
Numeric	7

Alerts

`year` has constant value "1970"	Constant
`city/district` is highly overall correlated with `landfill_capacity_(tons)` and 3 other fields	High correlation
`landfill_capacity_(tons)` is highly overall correlated with `city/district` and 2 other fields	High correlation
`landfill_location_(lat,_long)` is highly overall correlated with `city/district` and 3 other fields	High correlation
`landfill_name` is highly overall correlated with `city/district` and 3 other fields	High correlation
`population_density_(people/km²)` is highly overall correlated with `city/district` and 2 other fields	High correlation
`city/district` is uniformly distributed	Uniform
`waste_type` is uniformly distributed	Uniform
`landfill_name` is uniformly distributed	Uniform
`landfill_location_(lat,_long)` is uniformly distributed	Uniform
`awareness_campaigns_count` has 48 (5.6%) zeros	Zeros

Reproduction

Analysis started	2025-08-10 12:20:50.191510
Analysis finished	2025-08-10 12:20:58.016468
Duration	7.82 seconds
Software version	ydata-profiling vv4.16.1
Download configuration	config.json

city/district
Categorical

High correlation Uniform

Distinct	34
Distinct (%)	4.0%
Missing	0
Missing (%)	0.0%
Memory size	53.5 KiB

Mumbai	25
Delhi	25
Bengaluru	25
Chennai	25
Kolkata	25
Other values (29)	725

Length

Max length	18
Median length	10
Mean length	7.3529412
Min length	4

Characters and Unicode

Total characters	6,250
Distinct characters	39
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Mumbai
2nd row	Mumbai
3rd row	Mumbai
4th row	Mumbai
5th row	Mumbai

Common Values

Value	Count	Frequency (%)
Mumbai	25	2.9%
Delhi	25	2.9%
Bengaluru	25	2.9%
Chennai	25	2.9%
Kolkata	25	2.9%
Hyderabad	25	2.9%
Pune	25	2.9%
Ahmedabad	25	2.9%
Jaipur	25	2.9%
Lucknow	25	2.9%
Other values (24)	600	70.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
mumbai	25	2.9%
delhi	25	2.9%
bengaluru	25	2.9%
chennai	25	2.9%
kolkata	25	2.9%
hyderabad	25	2.9%
pune	25	2.9%
ahmedabad	25	2.9%
jaipur	25	2.9%
lucknow	25	2.9%
Other values (24)	600	70.6%

Most occurring characters

Value	Count	Frequency (%)
a	1200	19.2%
r	500	8.0%
u	425	6.8%
i	375	6.0%
n	350	5.6%
h	325	5.2%
d	275	4.4%
o	250	4.0%
t	250	4.0%
e	250	4.0%
Other values (29)	2050	32.8%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	6250	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	1200	19.2%
r	500	8.0%
u	425	6.8%
i	375	6.0%
n	350	5.6%
h	325	5.2%
d	275	4.4%
o	250	4.0%
t	250	4.0%
e	250	4.0%
Other values (29)	2050	32.8%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	6250	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	1200	19.2%
r	500	8.0%
u	425	6.8%
i	375	6.0%
n	350	5.6%
h	325	5.2%
d	275	4.4%
o	250	4.0%
t	250	4.0%
e	250	4.0%
Other values (29)	2050	32.8%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	6250	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	1200	19.2%
r	500	8.0%
u	425	6.8%
i	375	6.0%
n	350	5.6%
h	325	5.2%
d	275	4.4%
o	250	4.0%
t	250	4.0%
e	250	4.0%
Other values (29)	2050	32.8%

waste_type
Categorical

Uniform

Distinct	5
Distinct (%)	0.6%
Missing	0
Missing (%)	0.0%
Memory size	54.4 KiB

Plastic	170
Organic	170
E-Waste	170
Construction	170
Hazardous	170

Length

Max length	12
Median length	7
Mean length	8.4
Min length	7

Characters and Unicode

Total characters	7,140
Distinct characters	21
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Plastic
2nd row	Organic
3rd row	E-Waste
4th row	Construction
5th row	Hazardous

Common Values

Value	Count	Frequency (%)
Plastic	170	20.0%
Organic	170	20.0%
E-Waste	170	20.0%
Construction	170	20.0%
Hazardous	170	20.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
plastic	170	20.0%
organic	170	20.0%
e-waste	170	20.0%
construction	170	20.0%
hazardous	170	20.0%

Most occurring characters

Value	Count	Frequency (%)
a	850	11.9%
t	680	9.5%
s	680	9.5%
c	510	7.1%
i	510	7.1%
o	510	7.1%
n	510	7.1%
r	510	7.1%
u	340	4.8%
l	170	2.4%
Other values (11)	1870	26.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	7140	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	850	11.9%
t	680	9.5%
s	680	9.5%
c	510	7.1%
i	510	7.1%
o	510	7.1%
n	510	7.1%
r	510	7.1%
u	340	4.8%
l	170	2.4%
Other values (11)	1870	26.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	7140	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	850	11.9%
t	680	9.5%
s	680	9.5%
c	510	7.1%
i	510	7.1%
o	510	7.1%
n	510	7.1%
r	510	7.1%
u	340	4.8%
l	170	2.4%
Other values (11)	1870	26.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	7140	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	850	11.9%
t	680	9.5%
s	680	9.5%
c	510	7.1%
i	510	7.1%
o	510	7.1%
n	510	7.1%
r	510	7.1%
u	340	4.8%
l	170	2.4%
Other values (11)	1870	26.2%

waste_generated_(tons/day)
Real number (ℝ)

Distinct	807
Distinct (%)	94.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5262.2494

Minimum	511
Maximum	9980
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	6.8 KiB

Quantile statistics

Minimum	511
5-th percentile	875.05
Q1	2865.75
median	5283
Q3	7757.25
95-th percentile	9507.8
Maximum	9980
Range	9469
Interquartile range (IQR)	4891.5

Descriptive statistics

Standard deviation	2786.9847
Coefficient of variation (CV)	0.52961852
Kurtosis	-1.2255036
Mean	5262.2494
Median Absolute Deviation (MAD)	2442
Skewness	-0.023816513
Sum	4472912
Variance	7767283.9
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
5732	3	0.4%
7540	3	0.4%
1887	2	0.2%
4466	2	0.2%
2294	2	0.2%
6409	2	0.2%
3125	2	0.2%
4118	2	0.2%
4487	2	0.2%
1942	2	0.2%
Other values (797)	828	97.4%

Value	Count	Frequency (%)
511	1	0.1%
512	1	0.1%
525	1	0.1%
526	1	0.1%
528	1	0.1%
545	2	0.2%
549	2	0.2%
552	1	0.1%
558	1	0.1%
577	1	0.1%

Value	Count	Frequency (%)
9980	1	0.1%
9976	1	0.1%
9954	1	0.1%
9946	1	0.1%
9929	1	0.1%
9903	1	0.1%
9883	1	0.1%
9869	1	0.1%
9857	1	0.1%
9848	1	0.1%

recycling_rate_(%)
Real number (ℝ)

Distinct	56
Distinct (%)	6.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	57.076471

Minimum	30
Maximum	85
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	6.8 KiB

Quantile statistics

Minimum	30
5-th percentile	32
Q1	43
median	56
Q3	71
95-th percentile	82
Maximum	85
Range	55
Interquartile range (IQR)	28

Descriptive statistics

Standard deviation	16.129994
Coefficient of variation (CV)	0.28260322
Kurtosis	-1.1991203
Mean	57.076471
Median Absolute Deviation (MAD)	14
Skewness	0.026325494
Sum	48515
Variance	260.17671
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
36	26	3.1%
53	22	2.6%
69	21	2.5%
38	21	2.5%
55	20	2.4%
48	19	2.2%
54	19	2.2%
52	19	2.2%
61	19	2.2%
58	18	2.1%
Other values (46)	646	76.0%

Value	Count	Frequency (%)
30	15	1.8%
31	15	1.8%
32	16	1.9%
33	16	1.9%
34	15	1.8%
35	12	1.4%
36	26	3.1%
37	14	1.6%
38	21	2.5%
39	17	2.0%

Value	Count	Frequency (%)
85	17	2.0%
84	12	1.4%
83	12	1.4%
82	10	1.2%
81	18	2.1%
80	11	1.3%
79	18	2.1%
78	17	2.0%
77	17	2.0%
76	16	1.9%

population_density_(people/km²)
Real number (ℝ)

High correlation

Distinct	33
Distinct (%)	3.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	13489.706

Minimum	2335
Maximum	24032
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	6.8 KiB

Quantile statistics

Minimum	2335
5-th percentile	2929
Q1	7927
median	12579.5
Q3	19087
95-th percentile	23465
Maximum	24032
Range	21697
Interquartile range (IQR)	11160

Descriptive statistics

Standard deviation	6631.0815
Coefficient of variation (CV)	0.49156605
Kurtosis	-1.2359237
Mean	13489.706
Median Absolute Deviation (MAD)	5727
Skewness	-0.066472444
Sum	11466250
Variance	43971242
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=33)

Value	Count	Frequency (%)
2929	50	5.9%
11191	25	2.9%
14376	25	2.9%
21430	25	2.9%
18195	25	2.9%
7927	25	2.9%
12547	25	2.9%
9464	25	2.9%
17335	25	2.9%
2335	25	2.9%
Other values (23)	575	67.6%

Value	Count	Frequency (%)
2335	25	2.9%
2929	50	5.9%
4071	25	2.9%
4629	25	2.9%
6465	25	2.9%
7118	25	2.9%
7178	25	2.9%
7927	25	2.9%
7976	25	2.9%
8678	25	2.9%

Value	Count	Frequency (%)
24032	25	2.9%
23465	25	2.9%
23232	25	2.9%
22866	25	2.9%
21598	25	2.9%
21430	25	2.9%
19454	25	2.9%
19181	25	2.9%
19087	25	2.9%
18697	25	2.9%

municipal_efficiency_score_(1_10)
Real number (ℝ)

Distinct	6
Distinct (%)	0.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	7.4

Minimum	5
Maximum	10
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	6.8 KiB

Quantile statistics

Minimum	5
5-th percentile	5
Q1	6
median	7
Q3	9
95-th percentile	10
Maximum	10
Range	5
Interquartile range (IQR)	3

Descriptive statistics

Standard deviation	1.7221621
Coefficient of variation (CV)	0.2327246
Kurtosis	-1.3048067
Mean	7.4
Median Absolute Deviation (MAD)	2
Skewness	0.056862826
Sum	6290
Variance	2.9658422
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
5	159	18.7%
6	151	17.8%
9	148	17.4%
7	133	15.6%
8	132	15.5%
10	127	14.9%

Value	Count	Frequency (%)
5	159	18.7%
6	151	17.8%
7	133	15.6%
8	132	15.5%
9	148	17.4%
10	127	14.9%

Value	Count	Frequency (%)
10	127	14.9%
9	148	17.4%
8	132	15.5%
7	133	15.6%
6	151	17.8%
5	159	18.7%

disposal_method
Categorical

Distinct	4
Distinct (%)	0.5%
Missing	0
Missing (%)	0.0%
Memory size	55.5 KiB

Incineration	218
Recycling	213
Landfill	210
Composting	209

Length

Max length	12
Median length	10
Mean length	9.7682353
Min length	8

Characters and Unicode

Total characters	8,303
Distinct characters	20
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Composting
2nd row	Composting
3rd row	Incineration
4th row	Landfill
5th row	Recycling

Common Values

Value	Count	Frequency (%)
Incineration	218	25.6%
Recycling	213	25.1%
Landfill	210	24.7%
Composting	209	24.6%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
incineration	218	25.6%
recycling	213	25.1%
landfill	210	24.7%
composting	209	24.6%

Most occurring characters

Value	Count	Frequency (%)
n	1286	15.5%
i	1068	12.9%
c	644	7.8%
o	636	7.7%
l	633	7.6%
e	431	5.2%
a	428	5.2%
t	427	5.1%
g	422	5.1%
I	218	2.6%
Other values (10)	2110	25.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	8303	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
n	1286	15.5%
i	1068	12.9%
c	644	7.8%
o	636	7.7%
l	633	7.6%
e	431	5.2%
a	428	5.2%
t	427	5.1%
g	422	5.1%
I	218	2.6%
Other values (10)	2110	25.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	8303	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
n	1286	15.5%
i	1068	12.9%
c	644	7.8%
o	636	7.7%
l	633	7.6%
e	431	5.2%
a	428	5.2%
t	427	5.1%
g	422	5.1%
I	218	2.6%
Other values (10)	2110	25.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	8303	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
n	1286	15.5%
i	1068	12.9%
c	644	7.8%
o	636	7.7%
l	633	7.6%
e	431	5.2%
a	428	5.2%
t	427	5.1%
g	422	5.1%
I	218	2.6%
Other values (10)	2110	25.4%

cost_of_waste_management_(₹/ton)
Real number (ℝ)

Distinct	780
Distinct (%)	91.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2778.4588

Minimum	503
Maximum	4999
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	6.8 KiB

Quantile statistics

Minimum	503
5-th percentile	762.9
Q1	1647.5
median	2853
Q3	3855
95-th percentile	4733.2
Maximum	4999
Range	4496
Interquartile range (IQR)	2207.5

Descriptive statistics

Standard deviation	1276.3256
Coefficient of variation (CV)	0.4593646
Kurtosis	-1.1574327
Mean	2778.4588
Median Absolute Deviation (MAD)	1097
Skewness	-0.057412188
Sum	2361690
Variance	1629007.1
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
3131	3	0.4%
4725	3	0.4%
1093	3	0.4%
3000	3	0.4%
1084	3	0.4%
4307	3	0.4%
3888	2	0.2%
4938	2	0.2%
1687	2	0.2%
1135	2	0.2%
Other values (770)	824	96.9%

Value	Count	Frequency (%)
503	1	0.1%
509	1	0.1%
510	1	0.1%
516	2	0.2%
527	1	0.1%
533	1	0.1%
549	1	0.1%
550	2	0.2%
553	1	0.1%
557	1	0.1%

Value	Count	Frequency (%)
4999	1	0.1%
4993	1	0.1%
4988	1	0.1%
4978	2	0.2%
4975	1	0.1%
4966	1	0.1%
4958	1	0.1%
4952	2	0.2%
4944	1	0.1%
4941	1	0.1%

awareness_campaigns_count
Real number (ℝ)

Zeros

Distinct	21
Distinct (%)	2.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	9.9047059

Minimum	0
Maximum	20
Zeros	48
Zeros (%)	5.6%
Negative	0
Negative (%)	0.0%
Memory size	6.8 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	5
median	10
Q3	15
95-th percentile	19
Maximum	20
Range	20
Interquartile range (IQR)	10

Descriptive statistics

Standard deviation	6.0707724
Coefficient of variation (CV)	0.61291798
Kurtosis	-1.2160041
Mean	9.9047059
Median Absolute Deviation (MAD)	5
Skewness	-0.038929224
Sum	8419
Variance	36.854277
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=21)

Value	Count	Frequency (%)
11	50	5.9%
15	49	5.8%
0	48	5.6%
14	46	5.4%
17	45	5.3%
12	44	5.2%
1	43	5.1%
6	43	5.1%
13	42	4.9%
5	42	4.9%
Other values (11)	398	46.8%

Value	Count	Frequency (%)
0	48	5.6%
1	43	5.1%
2	40	4.7%
3	38	4.5%
4	41	4.8%
5	42	4.9%
6	43	5.1%
7	37	4.4%
8	30	3.5%
9	28	3.3%

Value	Count	Frequency (%)
20	37	4.4%
19	39	4.6%
18	28	3.3%
17	45	5.3%
16	41	4.8%
15	49	5.8%
14	46	5.4%
13	42	4.9%
12	44	5.2%
11	50	5.9%

landfill_name
Categorical

High correlation Uniform

Distinct	34
Distinct (%)	4.0%
Missing	0
Missing (%)	0.0%
Memory size	61.0 KiB

Mumbai Landfill	25
Delhi Landfill	25
Bengaluru Landfill	25
Chennai Landfill	25
Kolkata Landfill	25
Other values (29)	725

Length

Max length	27
Median length	19
Mean length	16.352941
Min length	13

Characters and Unicode

Total characters	13,900
Distinct characters	41
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Mumbai Landfill
2nd row	Mumbai Landfill
3rd row	Mumbai Landfill
4th row	Mumbai Landfill
5th row	Mumbai Landfill

Common Values

Value	Count	Frequency (%)
Mumbai Landfill	25	2.9%
Delhi Landfill	25	2.9%
Bengaluru Landfill	25	2.9%
Chennai Landfill	25	2.9%
Kolkata Landfill	25	2.9%
Hyderabad Landfill	25	2.9%
Pune Landfill	25	2.9%
Ahmedabad Landfill	25	2.9%
Jaipur Landfill	25	2.9%
Lucknow Landfill	25	2.9%
Other values (24)	600	70.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
landfill	850	50.0%
mumbai	25	1.5%
delhi	25	1.5%
bengaluru	25	1.5%
chennai	25	1.5%
kolkata	25	1.5%
hyderabad	25	1.5%
pune	25	1.5%
ahmedabad	25	1.5%
jaipur	25	1.5%
Other values (25)	625	36.8%

Most occurring characters

Value	Count	Frequency (%)
a	2050	14.7%
l	1900	13.7%
i	1225	8.8%
n	1200	8.6%
d	1125	8.1%
L	900	6.5%
f	850	6.1%
	850	6.1%
r	500	3.6%
u	425	3.1%
Other values (31)	2875	20.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	13900	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	2050	14.7%
l	1900	13.7%
i	1225	8.8%
n	1200	8.6%
d	1125	8.1%
L	900	6.5%
f	850	6.1%
	850	6.1%
r	500	3.6%
u	425	3.1%
Other values (31)	2875	20.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	13900	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	2050	14.7%
l	1900	13.7%
i	1225	8.8%
n	1200	8.6%
d	1125	8.1%
L	900	6.5%
f	850	6.1%
	850	6.1%
r	500	3.6%
u	425	3.1%
Other values (31)	2875	20.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	13900	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	2050	14.7%
l	1900	13.7%
i	1225	8.8%
n	1200	8.6%
d	1125	8.1%
L	900	6.5%
f	850	6.1%
	850	6.1%
r	500	3.6%
u	425	3.1%
Other values (31)	2875	20.7%

landfill_location_(lat,_long)
Categorical

High correlation Uniform

Distinct	34
Distinct (%)	4.0%
Missing	0
Missing (%)	0.0%
Memory size	60.5 KiB

22.4265, 77.4931	25
30.2591, 91.9376	25
15.7581, 85.4837	25
29.4633, 80.8873	25
16.068, 72.6096	25
Other values (29)	725

Length

Max length	16
Median length	16
Mean length	15.764706
Min length	15

Characters and Unicode

Total characters	13,400
Distinct characters	13
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	22.4265, 77.4931
2nd row	22.4265, 77.4931
3rd row	22.4265, 77.4931
4th row	22.4265, 77.4931
5th row	22.4265, 77.4931

Common Values

Value	Count	Frequency (%)
22.4265, 77.4931	25	2.9%
30.2591, 91.9376	25	2.9%
15.7581, 85.4837	25	2.9%
29.4633, 80.8873	25	2.9%
16.068, 72.6096	25	2.9%
34.069, 82.1518	25	2.9%
28.7237, 84.2278	25	2.9%
19.3868, 72.7845	25	2.9%
11.6909, 94.4267	25	2.9%
10.3904, 81.8808	25	2.9%
Other values (24)	600	70.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
22.4265	25	1.5%
77.4931	25	1.5%
30.2591	25	1.5%
91.9376	25	1.5%
15.7581	25	1.5%
85.4837	25	1.5%
29.4633	25	1.5%
80.8873	25	1.5%
16.068	25	1.5%
72.6096	25	1.5%
Other values (58)	1450	85.3%

Most occurring characters

Value	Count	Frequency (%)
.	1700	12.7%
8	1375	10.3%
1	1175	8.8%
3	1050	7.8%
9	1000	7.5%
6	975	7.3%
2	975	7.3%
7	950	7.1%
4	950	7.1%
5	875	6.5%
Other values (3)	2375	17.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	13400	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
.	1700	12.7%
8	1375	10.3%
1	1175	8.8%
3	1050	7.8%
9	1000	7.5%
6	975	7.3%
2	975	7.3%
7	950	7.1%
4	950	7.1%
5	875	6.5%
Other values (3)	2375	17.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	13400	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
.	1700	12.7%
8	1375	10.3%
1	1175	8.8%
3	1050	7.8%
9	1000	7.5%
6	975	7.3%
2	975	7.3%
7	950	7.1%
4	950	7.1%
5	875	6.5%
Other values (3)	2375	17.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	13400	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
.	1700	12.7%
8	1375	10.3%
1	1175	8.8%
3	1050	7.8%
9	1000	7.5%
6	975	7.3%
2	975	7.3%
7	950	7.1%
4	950	7.1%
5	875	6.5%
Other values (3)	2375	17.7%

landfill_capacity_(tons)
Real number (ℝ)

High correlation

Distinct	34
Distinct (%)	4.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	58934.618

Minimum	22690
Maximum	98646
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	6.8 KiB

Quantile statistics

Minimum	22690
5-th percentile	24927
Q1	45575
median	61038.5
Q3	71127
95-th percentile	98572
Maximum	98646
Range	75956
Interquartile range (IQR)	25552

Descriptive statistics

Standard deviation	19413.627
Coefficient of variation (CV)	0.32940957
Kurtosis	-0.59684302
Mean	58934.618
Median Absolute Deviation (MAD)	13246.5
Skewness	0.053472764
Sum	50094425
Variance	3.7688892 × 10⁸
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=34)

Value	Count	Frequency (%)
45575	25	2.9%
74509	25	2.9%
52609	25	2.9%
65486	25	2.9%
80985	25	2.9%
34239	25	2.9%
49524	25	2.9%
69399	25	2.9%
71127	25	2.9%
80251	25	2.9%
Other values (24)	600	70.6%

Value	Count	Frequency (%)
22690	25	2.9%
24927	25	2.9%
30373	25	2.9%
31477	25	2.9%
34239	25	2.9%
35432	25	2.9%
38471	25	2.9%
45318	25	2.9%
45575	25	2.9%
48016	25	2.9%

Value	Count	Frequency (%)
98646	25	2.9%
98572	25	2.9%
83130	25	2.9%
82082	25	2.9%
80985	25	2.9%
80251	25	2.9%
79314	25	2.9%
74509	25	2.9%
71127	25	2.9%
69399	25	2.9%

year
Categorical

Constant

Distinct	1
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	50.8 KiB

1970	850

Length

Max length	4
Median length	4
Mean length	4
Min length	4

Characters and Unicode

Total characters	3,400
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1970
2nd row	1970
3rd row	1970
4th row	1970
5th row	1970

Common Values

Value	Count	Frequency (%)
1970	850	100.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1970	850	100.0%

Most occurring characters

Value	Count	Frequency (%)
1	850	25.0%
9	850	25.0%
7	850	25.0%
0	850	25.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	3400	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
1	850	25.0%
9	850	25.0%
7	850	25.0%
0	850	25.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	3400	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
1	850	25.0%
9	850	25.0%
7	850	25.0%
0	850	25.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	3400	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
1	850	25.0%
9	850	25.0%
7	850	25.0%
0	850	25.0%

	awareness_campaigns_count	city/district	cost_of_waste_management_(₹/ton)	disposal_method	landfill_capacity_(tons)	landfill_location_(lat,_long)	landfill_name	municipal_efficiency_score_(1_10)	population_density_(people/km²)	recycling_rate_(%)	waste_generated_(tons/day)	waste_type
awareness_campaigns_count	1.000	0.000	-0.018	0.000	0.050	0.000	0.000	0.038	0.048	-0.018	-0.004	0.029
city/district	0.000	1.000	0.019	0.000	0.985	1.000	1.000	0.063	0.986	0.045	0.000	0.000
cost_of_waste_management_(₹/ton)	-0.018	0.019	1.000	0.000	-0.002	0.019	0.019	-0.070	-0.031	-0.004	0.042	0.000
disposal_method	0.000	0.000	0.000	1.000	0.000	0.000	0.000	0.000	0.000	0.049	0.036	0.000
landfill_capacity_(tons)	0.050	0.985	-0.002	0.000	1.000	0.985	0.985	0.067	-0.281	0.064	0.036	0.000
landfill_location_(lat,_long)	0.000	1.000	0.019	0.000	0.985	1.000	1.000	0.063	0.986	0.045	0.000	0.000
landfill_name	0.000	1.000	0.019	0.000	0.985	1.000	1.000	0.063	0.986	0.045	0.000	0.000
municipal_efficiency_score_(1_10)	0.038	0.063	-0.070	0.000	0.067	0.063	0.063	1.000	-0.086	-0.033	0.017	0.000
population_density_(people/km²)	0.048	0.986	-0.031	0.000	-0.281	0.986	0.986	-0.086	1.000	-0.053	0.001	0.000
recycling_rate_(%)	-0.018	0.045	-0.004	0.049	0.064	0.045	0.045	-0.033	-0.053	1.000	-0.034	0.035
waste_generated_(tons/day)	-0.004	0.000	0.042	0.036	0.036	0.000	0.000	0.017	0.001	-0.034	1.000	0.000
waste_type	0.029	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.035	0.000	1.000

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

	city/district	waste_type	waste_generated_(tons/day)	recycling_rate_(%)	population_density_(people/km²)	municipal_efficiency_score_(1_10)	disposal_method	cost_of_waste_management_(₹/ton)	awareness_campaigns_count	landfill_name	landfill_location_(lat,_long)	landfill_capacity_(tons)	year
0	Mumbai	Plastic	6610	68	11191	9	Composting	3056	14	Mumbai Landfill	22.4265, 77.4931	45575	1970
1	Mumbai	Organic	1181	56	11191	5	Composting	2778	12	Mumbai Landfill	22.4265, 77.4931	45575	1970
2	Mumbai	E-Waste	8162	53	11191	8	Incineration	3390	13	Mumbai Landfill	22.4265, 77.4931	45575	1970
3	Mumbai	Construction	8929	56	11191	5	Landfill	1498	14	Mumbai Landfill	22.4265, 77.4931	45575	1970
4	Mumbai	Hazardous	5032	44	11191	7	Recycling	2221	16	Mumbai Landfill	22.4265, 77.4931	45575	1970
5	Mumbai	Plastic	7456	73	11191	9	Landfill	3195	6	Mumbai Landfill	22.4265, 77.4931	45575	1970
6	Mumbai	Organic	7118	37	11191	6	Composting	3686	14	Mumbai Landfill	22.4265, 77.4931	45575	1970
7	Mumbai	E-Waste	9189	57	11191	10	Landfill	1791	12	Mumbai Landfill	22.4265, 77.4931	45575	1970
8	Mumbai	Construction	8609	48	11191	8	Incineration	1681	20	Mumbai Landfill	22.4265, 77.4931	45575	1970
9	Mumbai	Hazardous	6632	71	11191	6	Incineration	2311	12	Mumbai Landfill	22.4265, 77.4931	45575	1970

	city/district	waste_type	waste_generated_(tons/day)	recycling_rate_(%)	population_density_(people/km²)	municipal_efficiency_score_(1_10)	disposal_method	cost_of_waste_management_(₹/ton)	awareness_campaigns_count	landfill_name	landfill_location_(lat,_long)	landfill_capacity_(tons)	year
840	Gwalior	Plastic	3556	41	11280	10	Incineration	4042	2	Gwalior Landfill	10.9566, 91.6565	54460	1970
841	Gwalior	Organic	9726	50	11280	10	Recycling	4444	7	Gwalior Landfill	10.9566, 91.6565	54460	1970
842	Gwalior	E-Waste	5300	60	11280	5	Composting	669	15	Gwalior Landfill	10.9566, 91.6565	54460	1970
843	Gwalior	Construction	7561	47	11280	8	Composting	3024	18	Gwalior Landfill	10.9566, 91.6565	54460	1970
844	Gwalior	Hazardous	4272	41	11280	6	Incineration	4123	9	Gwalior Landfill	10.9566, 91.6565	54460	1970
845	Gwalior	Plastic	6842	42	11280	8	Recycling	3546	15	Gwalior Landfill	10.9566, 91.6565	54460	1970
846	Gwalior	Organic	5233	38	11280	10	Recycling	1146	5	Gwalior Landfill	10.9566, 91.6565	54460	1970
847	Gwalior	E-Waste	9903	41	11280	7	Landfill	3260	4	Gwalior Landfill	10.9566, 91.6565	54460	1970
848	Gwalior	Construction	7540	77	11280	6	Composting	4220	7	Gwalior Landfill	10.9566, 91.6565	54460	1970
849	Gwalior	Hazardous	2480	58	11280	6	Composting	1081	19	Gwalior Landfill	10.9566, 91.6565	54460	1970

Overview

Variables

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Interactions

Correlations

Missing values